bioRxivImmunologyPreprint
B Cells Promote T Cell Immunosenescence and Mammalian Aging Parameters
S. Khan, M. Chakraborty, F. Wu, N. Chen, T. Wang, Y. T. Chan, A. Sayad, J.-D. S. Vasquez, M. Kotlyar, K. Nguyen, Y. Huang, F. J. Alibhai, M. Woo, R.-K. Li, M. Husain, I. Jurisica, A. J. Gehring, P. S. Ohashi, D. Furman, S. Tsai, S. Winer, D. A. Winer
Abstract
A dysregulated adaptive immune system is a key feature of aging, and is associated with age-related chronic diseases and mortality. Most notably, aging is linked to a loss in the diversity of the T cell repertoire and expansion of activated inflammatory age-related T cell subsets, though the main drivers of these processes are largely unknown. Here, we find that T cell aging is directly influenced by B cells. Using multiple models of B cell manipulation and single-cell omics, we find B cells to be a major cell type that is largely responsible for the age-related reduction of naive T cells, their associated differentiation towards pathogenic immunosenescent T cell subsets, and for the clonal restriction of their T cell receptor (TCR). Accordingly, we find that these pathogenic shifts can be therapeutically targeted via CD20 monoclonal antibody treatment. Mechanistically, we uncover a new role for insulin receptor signaling in influencing age-related B cell pathogenicity that in turn induces T cell dysfunction and a decline in healthspan parameters. These results establish B cells as a pivotal force contributing to age-associated adaptive immune dysfunction and healthspan outcomes, and suggest new modalities to manage aging and related multi-morbidity. One Sentence SummaryInsulin receptor signaling facilitates the induction of age associated B cell inflammatory changes, which drive phenotypic aging of the T cell compartment and adverse outcomes to mammalian healthspan parameters.
- organism: mouse
- assay: bulk RNA-seq
- assay: multiome
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- research focus: drug response / drug discovery
- approach: experimental assay
- approach: statistical model
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